Risk of infection and appeal to public benefit increase compliance with infection control measures

To handle an infectious outbreak, the public must be informed about the infection risk and be motivated to comply with infection control measures. Perceiving the situation as threatening and seeing public benefits to complying may increase the public’s motivation to comply. The current study used a preregistered survey experiment to investigate if emphasizing high infection risk and appealing to societal benefits impacted intention to comply with infection control measures. The results show main effects of risk and of appeals to societal benefits. There was no interaction between risk scenario and motivational emphasis. The results suggest that to maximize compliance, information about disease outbreak should emphasize the individual risk of contracting the disease, and could also underline the public value of limiting infection spread. These findings can inform communication strategies during an infectious disease outbreak and help health authorities limit transmission.

Establishment of Virtual-Reality-Based Safety Education and Training System for Safety Engagement

The current safety education and training system has a number of problems, namely that the actual risks in the field are not reflected and that workers cannot be engaged in safety education. Therefore, we conducted a study to build a VR-based safety education system that reflects the problems actually occurring in the field. The risk points of the electrical construction sites were derived through in-depth interviews with various stakeholders such as field workers, safety managers, and management. A risk scenario was also constructed by analyzing the causes and effects of existing accident cases. A safety education system was constructed to which the established risk scenario was applied. In the virtual construction site, the site’s own model, safety equipment, and members were implemented in a 3D model to form a virtual reality environment. This environment is intended to provide an educational environment wherein workers can immerse themselves in safety, specifically because this VR-based environment can induce active participation by providing safety information through various experiences. In addition, in this study, a VR-based safety education system that reflects the field conditions was designed to prepare basic data for the modernization and activation of safety education.

Methodology for Assessment of Economic and Environmental Losses in High Threat Objects

The Doctoral Thesis is dedicated to the development of methodology for assessing economic and environmental losses in high-risk objects. Effective assessment methods increase the safety levels and help prepare for potential accidents involving uncontrolled release of a large energy stock and predict the extent of potential loss in the event of an emergency. As part of this paper, modelling of the hazards causing accidents and compiling global emergency statistics has been carried out. The author has developed a useful, innovative methodology for the calculation of environmental and economic losses, so that all stakeholders, without investing large time resources, can obtain reliable and reasonable results. The current risk assessment methods have been summarised in the paper, and their shortcomings and benefits have been evaluated. The correlation between the depreciation of objects and the increase in the frequency of emergency situations have been analysed in the paper, as well as the proposals for reducing risks during the operational life of the site have been developed and the proposed methodology for assessing losses caused by a potential accident has been offered. The hazard assessment methodology proposed by the author is based on a probit function model that so far has been used very rarely in Latvia. As part of the Doctoral Thesis, the probit model constants have been tested using different scenarios for possible accidents in the calculation. The methodology algorithm developed by the author is innovative and consists of 6 core blocks: identification of the risk scenario; parameters depending on the surroundings and external meteorological conditions of the high-risk object (HRO); possible risk scenarios and modelling of their probability; identification of negative environmental effects; calculation of probability using the probit model and the assessment of economic and environmental losses. The executing algorithm of the proposed core blocks is closely linked to the efficiency theory as a sequence of operations and the adoption of effective management decisions, based on the procedure carried out, where different types of data are collected. Using the proposed methodology developed by the author, it is possible to establish the level of risk at the objects concerned and to foresee potential economic and environmental losses in the event of an accident. The proposed methodology can be used both at the design stage of the installation and in the existing high-risk objects. This paper provides a detailed example of the calculation that can be used as a sample.

Risk Analysis on PMMA Recycling Economics

Poly(methyl methacrylate) (PMMA) is a versatile polymer with a forecast market of 4 Mtons/y by 2025, and 6 USD billion by 2027. Each year, 10% of the produced cast sheets, extrusion sheets, or granules PMMA end up as post-production waste, accounting for approximately 30 000 tons/y in Europe only. To guide the future recycling efforts, we investigated the risks of depolymerization process economics for different PMMA scraps feedstock, capital expenditure (CAPEX), and regenerated MMA (r-MMA) prices via a Monte-Carlo simulation. An analysis of plastic recycling plants operating with similar technologies confirmed how a maximum 10 M USD plant (median cost) is what a company should aim for, based on our hypothesis. The capital investment and the r-MMA quality have the main impacts on the profitability. Depending on the pursued outcome, we identified three most suitable scenarios. Lower capital-intensive plants (Scenarios 4 and 8) provide the fastest payback time, but this generates a lower quality monomer, and therefore lower appeal on the long term. On 10 or 20 years of operation, companies should target the very best r-MMA quality, to achieve the highest net present value (Scenario 6). Product quality comes from the feedstock choice, depolymerization, and purification technologies. Counterintuitively, a plant processing low quality scraps available for free (Scenario 7), and therefore producing low purity r-MMA, has the highest probability of negative net present value after 10 years of operation, making it a high-risk scenario. Western countries (especially Europe), call for more and more pure r-MMA, hopefully comparable to the virgin material. With legislations on recycled products becoming more stringent, low quality product might not find a market in the future. To convince shareholders and government bodies, companies should demonstrate how funds and subsidies directly translate into higher quality products (more attractive to costumers), more economically viable, and with a wider market.

The Effect of COVID-19 to Credit Risk and Capital Risk of State-Owned Bank in Indonesia: A System Dynamics Model

The global COVID-19 pandemic has greatly affected people, especially in the economic and banking sectors. The Indonesian Financial Services Authority (Otoritas Jasa Keuangan, OJK) issued a credit restructuring policy, effective from March 2020 to March 2022, to reduce credit and bank capital risk. This study proposes the bank risk scenario after the credit restructuring policy of the OJK moratorium in March 2022 and proposes the internal bank policy simulation to mitigate credit and capital risks in terms of Non-Performing Loan (NPL) and Capital Adequacy Ratio (CAR). The difficulty of this study is how to develop the risk scenario and to simulate the bank risk mitigation policy after the policy moratorium, while the COVID-19 pandemic is still ongoing and the economy is not yet normal. To that purpose, this study uses a system dynamics methodology with Powersim Studio 10© software that is able to make scenarios on the level of credit risk (NPL) and bank capital (CAR) and able to simulate internal bank policy to overcome the risk by considering the environmental and policy changes. Based on the policy simulation, it is recommended that bank can implement the restructuring policy to control the credit risk and strengthening the NPL monitoring activity in order to manage and decrease the loan impairment expenses. To increase CAR, the result shows that the combined policy consists of the NPL monitoring program, the interest rate and the operating cost management program is able to produce a significant increase in bank’s capital (CAR). The original contribution of this study is to provide new model of credit and capital risk scenario and risk mitigation simulation during the COVID-19 pandemic. The advantage of this study is that the model can be tested and implemented to other banks.

Sometimes It’s Personal: Differential Outcomes of Person vs. Job at Risk Threats to Job Security

The current paper expands an under-addressed concept within the job insecurity literature, namely, whether threats to job security are specific to the jobholder (person-at-risk threats) or specific to the job (job-at-risk threats). Using a between-person experimental vignette design, 136 employed participants were asked to imagine themselves in either a Person-at-Risk or a Job-at-Risk scenario. As expected, participants in a person-at-risk scenario indicated more negative reactions to job insecurity, as captured by greater anticipated negative affect and poorer perceived social exchanges and organization-based self-esteem. They also reported reduced intention for interpersonal citizenship behavior and greater intention to engage in one form of impression management compared to individuals in a job-at-risk scenario. We interpret these findings in terms of their implications on individual versus group identity, as well as on well-being and the behavioral consequences of job insecurity.

Tail Conditional Expectations Based on Kumaraswamy Dispersion Models

Recently, there seems to be an increasing amount of interest in the use of the tail conditional expectation (TCE) as a useful measure of risk associated with a production process, for example, in the measurement of risk associated with stock returns corresponding to the manufacturing industry, such as the production of electric bulbs, investment in housing development, and financial institutions offering loans to small-scale industries. Companies typically face three types of risk (and associated losses from each of these sources): strategic (S); operational (O); and financial (F) (insurance companies additionally face insurance risks) and they come from multiple sources. For asymmetric and bounded losses (properly adjusted as necessary) that are continuous in nature, we conjecture that risk assessment measures via univariate/bivariate Kumaraswamy distribution will be efficient in the sense that the resulting TCE based on bivariate Kumaraswamy type copulas do not depend on the marginals. In fact, almost all classical measures of tail dependence are such, but they investigate the amount of tail dependence along the main diagonal of copulas, which has often little in common with the concentration of extremes in the copula’s domain of definition. In this article, we examined the above risk measure in the case of a univariate and bivariate Kumaraswamy (KW) portfolio risk, and computed TCE based on bivariate KW type copulas. For illustrative purposes, a well-known Stock indices data set was re-analyzed by computing TCE for the bivariate KW type copulas to determine which pairs produce minimum risk in a two-component risk scenario.